mlsanityData to 14 Oct 2026

Analog forecasting of extreme-causing weather patterns using deep learning

arXiv 1907.11617 ↗First posted 26 Jul 2019physics.ao-ph cs.LGcited by 33

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Abstract (arXiv)

Numerical weather prediction (NWP) models require ever-growing computing time/resources, but still, have difficulties with predicting weather extremes. Here we introduce a data-driven framework that is based on analog forecasting (prediction using past similar patterns) and employs a novel deep learning pattern-recognition technique (capsule neural networks, CapsNets) and impact-based auto-labeling strategy. CapsNets are trained on mid-tropospheric large-scale circulation patterns (Z500) labeled 0-4 depending on the existence and geographical region of surface temperature extremes over North America several days ahead. The trained networks predict the occurrence/region of cold or heat waves, only using Z500, with accuracies (recalls) of 69%-45% (77%-48%) or 62%-41% (73%-47%) 1-5 days ahead. CapsNets outperform simpler techniques such as convolutional neural networks and logistic regression. Using both temperature and Z500, accuracies (recalls) with CapsNets increase to ~ 80% (88%), showing the promises of multi-modal data-driven frameworks for accurate/fast extreme weather predictions, which can augment NWP efforts in providing early warnings.

Key facts. Cited by 33 papers in the map (data through 14 Oct 2026). First posted on arXiv 26 Jul 2019.

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Citing papers per year: 2021: 5; 2022: 7; 2023: 6; 2024: 8; 2025: 5; 2026: 2.

33 papers.

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  1. 2022FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operatorscited by 776
  2. 2023Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Datacited by 40
  3. 2024Can AI weather models predict out-of-distribution gray swan tropical cyclones?cited by 26
  4. 2023OceanNet: A principled neural operator-based digital twin for regional oceanscited by 24
  5. 2021Towards physically consistent data-driven weather forecasting: Integrating data assimilation with equivariance-preserving deep spatial transformerscited by 15
  6. 2021Data-driven geophysical forecasting: Simple, low-cost, and accurate baselines with kernel methodscited by 15
  7. 2024When are dynamical systems learned from time series data statistically accurate?cited by 15
  8. 2022Global Extreme Heat Forecasting Using Neural Weather Modelscited by 13
  9. 2021Deep Learning-based Extreme Heatwave Forecastcited by 9
  10. 2023Inexact iterative numerical linear algebra for neural network-based spectral estimation and rare-event predictioncited by 9
  11. 2022Long-term stability and generalization of observationally-constrained stochastic data-driven models for geophysical turbulencecited by 8
  12. 2022Probabilistic forecasts of extreme heatwaves using convolutional neural networks in a regime of lack of datacited by 7
21 more
  1. 2021Discovery of interpretable structural model errors by combining Bayesian sparse regression and data assimilation: A chaotic Kuramoto-Sivashinsky test casecited by 6
  2. 2023Deep Learning Techniques in Extreme Weather Events: A Reviewcited by 5
  3. 2024Tackling the Accuracy-Interpretability Trade-off in a Hierarchy of Machine Learning Models for the Prediction of Extreme Heatwavescited by 4
  4. 2021Model-assisted deep learning of rare extreme events from partial observationscited by 3
  5. 2022Analysis, Characterization, Prediction and Attribution of Extreme Atmospheric Events with Machine Learning: a Reviewcited by 3
  6. 2023Inductive biases in deep learning models for weather predictioncited by 3
  7. 2023Extreme heatwave sampling and prediction with analog Markov chain and comparisons with deep learningcited by 3
  8. 2024Using Deep Learning to Identify Initial Error Sensitivity for Interpretable ENSO Forecastscited by 3
  9. 2024AI for Extreme Event Modeling and Understanding: Methodologies and Challengescited by 3
  10. 2025Uncertainty propagation in feed-forward neural network modelscited by 3
  11. 2025AI-boosted rare event sampling to characterize extreme weathercited by 3
  12. 2025From Black Box to Insight: Explainable AI for Extreme Event Preparednesscited by 3
  13. 2024Harnessing Artificial Intelligence for Sustainable Agricultural Development in Africa: Opportunities, Challenges, and Impactcited by 2
  14. 2025Generative forecasting with joint probability modelscited by 2
  15. 2026Dynamics-Informed Deep Learning for Predicting Extreme Eventscited by 2
  16. 2022Extreme precipitation forecasting using attention augmented convolutionscited by 1
  17. 2022Accurate Long-term Air Temperature Prediction with a Fusion of Artificial Intelligence and Data Reduction Techniquescited by 1
  18. 2024Advancing Heatwave Forecasting via Distribution Informed-Graph Neural Networks (DI-GNNs): Integrating Extreme Value Theory with GNNscited by 1
  19. 2024DUNE: A Machine Learning Deep UNet++ based Ensemble Approach to Monthly, Seasonal and Annual Climate Forecastingcited by 0
  20. 2025Analogue Forecast System for Daily Precipitation Prediction Using Autoencoder Feature Extraction: Application in Hong Kongcited by 0
  21. 2026A Spatio-Temporal Deep Learning Approach For High-Resolution Gridded Monsoon Predictioncited by 0